Triple
T38261646
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | 42 Prague |
E1017942
|
entity |
| Predicate | hasIndustryConnections |
P110684
|
FINISHED |
| Object | yes |
—
|
LITERAL FINISHED |
How this triple was built (2 steps)
Every LLM step that produced this triple, in pipeline order — named-entity classification, the disambiguation choices (the exact options shown, with the pick highlighted), and the generated description. The batch + timestamp of each is in the Provenance table below.
NER
Named-entity recognition
gpt-5-mini
Instruction
Given a phrase, classify it is english named entity (e.g., persons, organizations, works of art) in Latin script, or not (e.g., literals, dates, URLs, verbose phrases). For disambiguation, the statement where the phrase occurs as object is also given. Please return a JSON object with `phrase` (string, the phrase being analyzed) and `is_ne` (boolean, indicating whether the phrase is a Named Entity).
Input
Phrase: yes | Statement: [42 Prague, hasIndustryConnections, yes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasIndustryConnections Context triple: [42 Prague, hasIndustryConnections, yes]
-
A.
hasIndustryTies
chosen
Indicates that an entity maintains professional, financial, or organizational connections with a particular industry or sector.
-
B.
industryConnection
Indicates a professional or business relationship linking entities within the same or related industries, such as partnerships, collaborations, or shared sector involvement.
-
C.
hasIndustryRole
Indicates that an entity holds or performs a specific role, function, or position within a particular industry or sector.
-
D.
hasIndustryPartnerships
Indicates that an entity maintains formal collaborative or cooperative relationships with organizations in a particular industry.
-
E.
hasIndustrySection
Indicates that an entity belongs to, is categorized under, or is associated with a particular industry section.
- F. None of above.
Provenance (3 batches)
The batch behind each pipeline step, in order, with when it ran. Timestamps are batch-level — stages were processed in waves, so the object chain (NER → NED1 → NEDg → NED2) reads in order, but predicate / elicitation batches can sit in a different wave.
| Step | Stage | Batch ID | Status | When |
|---|---|---|---|---|
| creating | Elicitation | batch_69f76de33e4481909099fa812709bd42 |
completed | May 3, 2026, 3:46 p.m. |
| NER | Named-entity recognition | batch_6a014a0b57dc8190b04ce51156ab95fa |
completed | May 11, 2026, 3:16 a.m. |
| PD | Predicate disambiguation | batch_6a0149afa57c8190a83257085766d916 |
completed | May 11, 2026, 3:14 a.m. |
Created at: May 3, 2026, 4:30 p.m.